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Best Practices for Fabless Semiconductor Firms – Part I October 30, 2007

Posted by Jeff in Business.
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Introduction

Best Practices are those methods, processes, activities, or techniques that have been found to be most effective at generating a desired outcome.  By implementing best practices, an organization may operate more effectively.  With best practices, over time and across an organization, the results can be substantial, with both improvements in execution and reduction in training.

Best practices are typically determined by review and analysis, and often with aspects of trial and error experimentation.  The steps can be broken down as follows:

  • Assessment of current practices
  • Applying quantitative benchmarks to the measurement of practices
  • Analysis of costs and benefits of practices
  • Selection of the best practice and revision of the current practice

We should note, however, that best practices are under constant review and revision.  Changes in technologies or markets can have a major impact and allow new practices to be developed that are more effective.  Specific areas of change within the semiconductor industry include:

  • Wafer size
  • Automation level
  • Outsourcing
  • Technology

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Collaborative Decision Environments are an Upcoming Trend October 17, 2007

Posted by Jeff in Business, collaboration, Technology.
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Last month, we mentioned a meeting with Bob Parker of Manufacturing Insights in which a number of trends in Enterprise Software were mentioned.  Bob recently published a perspective document in which he grouped a number of important concepts under the term “Collaborative Decision Environments”.  Many of the concepts were initially featured in an interview with Bob that appeared in Supply Demand Chain Exec Magazine earlier this year on predictions for 2007.

Examples that he gave included Teradata, SAS, Business Objects, and Oracle.  All of these firms are fielding products for collaboration and decision-making.  Within such a product, one can review and analyze data, and share aspects of the conclusions.

This was the first time that we have seen the concept applied directly in manufacturing.  Many of the prior examples were drawn from emergency situation handling, such as handling responses to natural disasters.

Here are some of the important characteristics of a CDE:

  • Provide shared access to a baseline content set.
  • Provide means to propose changes to the content.
  • Allow users to navigate through a sequence of changes, and commit or retract them within scenarios.
  • Define problems to be addressed, or goals to be accomplished and have them be used to set the context of the decision.
  • Provide semantic resolution of terms within disparate data sources.  In the manufacturing operations world, this would be a harmonized view of key content such as suppliers, products, assets, customers, and employees.
  • Provide analytic functions that allow evaluation of current or proposed data in terms of the problems or goals. This capability should include the ability to perform analytics that are retrospective (what happened), perspective (what is happening), or predictive (what will happen).
  • Provide a social network or ecosystem, within with participants can rank the relevance or ranking of comments, changes, and contributors, again in terms of the goals.  This enables the network or ecosystem to determine where expertise is located, and to expand to include additional experts or knowledge.

Not covered on this list are some of the communications technologies, such as having instant message or video collaboration.  We see those as being important as well, but they stem from infrastructure technologies outside of computational decision-making process that we are focused on.

It hasn’t appeared in the material from analysts yet, but it was clear from our discussion with Bob that Serus is also providing an example of a Collaborative Decision Environment.  This is mentioned in our posting on our Decision Support Infrastructure Architecture from earlier this month.  Over the next month, we will be clarifying more of the terms defined here and improving the alignment.

Notes on Enterprise Software Architecture – Part III October 12, 2007

Posted by Jeff in bpm, Business, collaboration, enterprise 2.0, Technology.
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In our previous postings we looked at definitions, then at the structure of Enterprise Systems Architecture, and Enterprise Application Architecture.  In this posting, we go beyond the typical definitions, and look at some of the challenges that we have been addressing at Serus, and what their impact has been on our architecture.  We also discuss the definition and impact of Enterprise 2.0 technologies.

Serus is focused on the evolution of enterprise software architecture toward operations management.  This category of software deals with supporting the ongoing decision-making of schedulers, planners, manufacturing operations staff and managers, etc.  (more…)

Decision Support Information Architecture October 8, 2007

Posted by Jeff in collaboration, enterprise 2.0, Technology.
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We view the Serus core information architecture as a “federated content hub for decision support”.  It has the following layers:

Decision Support Information Architecture

This model of content and operations on content appears ideally suited to solutions that are based on integrated information. It combines several aspects of reporting and business intelligence with the business process driven concepts.

There are several important layers:

Content Management: this focuses on the raw representation of fetched or received content.

Decision Management: this deals with deriving new information, or setting aside information or changes to values as part of scenarios.

Goal-Driven Analysis: this deals with creating search routines that will consider different options, toward improving an objective function score.  The objective function might be lowest cost, might be shortest delay, etc.

Presentation: this deals with the screen-building and screen navigation that allows the user to access information at each of the different levels below, from row data to particular scenarios.

Notes on Enterprise Software Architecture – Part II October 5, 2007

Posted by Jeff in bpm, collaboration, enterprise 2.0, Technology.
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In our previous posting, we reviewed some basic definitions, and divided the problem down into Enterprise Systems Architecture and Enterprise Application Architecture.  In this post, we deal with the latter.

Enterprise Application Architecture deals with the structure inside the application.  It covers aspects such as how the application connects with data bases and other data sources, how the business logic is organized, and how the presentation logic is organized.  As is typically the case, with increased decoupling of these layers of the design, the flexibility and maintainability of the application is greatly increased.

It is within EAA that the concepts of software organization known as “Design Patterns” apply.  This refers to a set of canonically-reused structures within software that have been identified and refined.  The first literature on this concept came out in the mid-1990’s. (more…)

Serus Presented at Enterprise 2.0 Mashups Summit October 1, 2007

Posted by Jeff in collaboration, enterprise 2.0, Event Reporting, Technology.
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Last Friday’s Enterprise 2.0 Mashups Summit was a very informative and interesting event.  There were presentations by most of the major players in the mashup technology or mashup infrastructure space, as well as presentations that focused on the API’s of the major information providers such as Google.

Near the end of the day, Serus gave a presentation titled “Enterprise Mashups for Outsourced Manufacturing: mashing your shipments and processes”.  This was appropriate placement, because we were the only presenter covering a usage case study.  After that was a panel in which the speakers compared thoughts on acceptance and effectiveness of mashups and content integration.

The theme that I noticed throughout the day was the challenge of trying to clarify the difference between a true “mashup”, and a “composite application”. In general, the conclusion was that a “mashup” is a content integration constructed by an end user using some tools, while “composite applications” are applications that include content integration and mashups, along with related concepts, but may not be as end-user oriented, and in fact may be built by the IT organization. (more…)